White Paper: How can Customs better leverage emerging AI technologies?

Discover how customs can better leverage emerging AI technologies for more sustainable and smarter operations in Cotecna's whitepaper.

Abstract 

Technological innovation is happening at a faster pace than ever before, creating new opportunities as well as challenges for many industries. This research paper aims to contribute to the efforts deployed by many customs administrations to leverage artificial intelligence (AI) driven technologies in order to support smarter operations and efficiency. It makes recommendations to identify the organizational processes that could benefit from AI and machine learning (ML) based initiatives.

The result of this paper is a set of practical frameworks coupled with technical, organizational and policy recommendations, which form a coherent business innovation kit to assist customs administrations to successfully start or scale their digital transformation journey.

Key Takeaways

The paper is comprised of three parts:

  • The first part suggests a practical and simple guideline to map AI-driven technologies values with the key customs processes, challenges and desired benefits, which identifies relevant cases that could benefit from AI-based initiatives.
  • The second part describes a framework that enables customs administrations to design and frame new ways to pursue modernization projects.
  • Finally, the third part highlights the technical considerations and requirements and makes organizational and policy recommendations to ensure a successful implementation of AI technologies.

About the Author 

Ismael Kafando is a statistics and econometrics engineer with over 14 years’ experience in working with Customs and managing the conception and implementation of data analytics and risk management products for the use in Customs and trade environment. He displays solid professional expertise on both the systems conception and implementation side, as well as the delivery and the client capacity building side.

This paper was first published in Word Custom Journal, Volume 14, Number 2.